Application of machine learning in soil heavy metals pollution assessment in the southeastern Tibetan plateau

Application of machine learning in soil heavy metals pollution assessment in the southeastern Tibetan plateau

Abstract The Tibetan Plateau, a globally significant ecological region, is experiencing escalating pollution from heavy metals (HMs). This study applies a machine learning approach based on the self-organizing map hyper-clustering, alongside advanced methodologies such as Positive Matrix Factorizati...

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Bibliographic Details
Main Authors: Yan Li, Yilong Yu, Shiyuan Ding, Wenjing Dai, Rongguang Shi, Gaoyang Cui, Xiaodong Li
Format: Article
Language:English
Published: Nature Portfolio 2025-04-01
Series:Scientific Reports
Subjects:
Self-Organizing map
HMs source
Improved Potential Ecological Risk Index
BiLISA analysis
Interaction risk
Online Access:https://doi.org/10.1038/s41598-025-97006-2
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https://doi.org/10.1038/s41598-025-97006-2

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